Development of an Information System for Personnel Management in Schools under the Surat Thani Primary Educational Service Area Office
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
This research aimed to develop and evaluate an Information System for Personnel Management (ISPM) tailored for schools under the Surat Thani Primary Educational Service Area Office. Employing a research and development (R&D) methodology, the study was conducted in three phases: (1) a needs analysis through in-depth interviews with 12 school administrators to identify problems and system requirements; (2) system development using the System Development Life Cycle (SDLC) model, followed by expert validation from seven IT professionals; and (3) implementation and effectiveness evaluation with 17 school personnel over a one-month trial. Results from Phase 1 indicated fragmented and inefficient practices, with most schools relying on manual or semi-digital tools. In Phase 2, the developed system was rated highly appropriate across dimensions such as data security (M = 4.95, SD = 0.53) and usability (M = 4.83, SD = 0.38). Phase 3 findings confirmed the system’s effectiveness, with an overall satisfaction rating of M = 4.82 (SD = 0.37). The study contributes to the field by offering a full-cycle model of ISPM development grounded in actual school needs and validated through expert and end-user feedback. Limitations include the restricted trial scope and short duration, suggesting the need for future research on scalability and long-term use. The system provides a practical solution for enhancing personnel data management in Thai schools and potentially across broader educational contexts.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it